Preliminary design and evaluation of a remote tele-mentoring system for minimally invasive surgery.

BACKGROUND: Tele-mentoring during surgery facilitates the transfer of surgical knowledge from a mentor (specialist surgeon) to a mentee (operating surgeon). The aim of this work is to develop a tele-mentoring system tailored for minimally invasive surgery (MIS) where the mentor can remotely demonstrate to the mentee the required motion of the surgical instruments. METHODS: A remote tele-mentoring system is implemented that generates visual cues in the form of virtual surgical instrument motion overlaid onto the live view of the operative field. The technical performance of the system is evaluated in a simulated environment, where the operating room and the central location of the mentor were physically located in different countries and connected over the internet. In addition, a user study was performed to assess the system as a mentoring tool. RESULTS: On average, it took 260 ms to send a view of the operative field of 1920 × 1080 resolution from the operating room to the central location of the mentor and an average of 132 ms to receive the motion of virtual surgical instruments from the central location to the operating room. The user study showed that it is feasible for the mentor to demonstrate and for the mentee to understand and replicate the motion of surgical instruments. CONCLUSION: The work demonstrates the feasibility of transferring information over the internet from a mentor to a mentee in the form of virtual surgical instruments. Their motion is overlaid onto the live view of the operative field enabling real-time interactions between both the surgeons.

Practical utility of liver segmentation methods in clinical surgeries and interventions.

Clinical imaging (e.g., magnetic resonance imaging and computed tomography) is a crucial adjunct for clinicians, aiding in the diagnosis of diseases and planning of appropriate interventions. This is especially true in malignant conditions such as hepatocellular carcinoma (HCC), where image segmentation (such as accurate delineation of liver and tumor) is the preliminary step taken by the clinicians to optimize diagnosis, staging, and treatment planning and intervention (e.g., transplantation, surgical resection, radiotherapy, PVE, embolization, etc). Thus, segmentation methods could potentially impact the diagnosis and treatment outcomes. This paper comprehensively reviews the literature (during the year 2012-2021) for relevant segmentation methods and proposes a broad categorization based on their clinical utility (i.e., surgical and radiological interventions) in HCC. The categorization is based on the parameters such as precision, accuracy, and automation.

Preliminary design of an actuated imaging probe for generation of additional visual cues in a robotic surgery.

BACKGROUND: The aim of this study was to enhance the visual feedback of surgeons, during robotic surgeries, by designing and developing an actuated 2D imaging probe, which is used in conjunction with the traditional stereoscopic camera of the da Vinci surgical system. The probe provides the surgeon with additional visual cues, overcoming visualization constraints encountered during certain scenarios of robot-assisted minimally invasive surgery. METHODS: The actuated imaging probe is implemented as a master-slave tele-manipulated system, and it is designed to be compatible with the da Vinci surgical system. The detachable probe design enables it to be mounted on any of the EndoWrist(®) instruments of the robot and is controlled by the surgeon using a custom-made pedal system. The image from the 2D probe is rendered along with the stereoscopic view on the surgeon's console. RESULTS: The experimental results demonstrate the effectiveness of the proposed actuated imaging probe when used as an additional visualization channel and in surgical scenarios presenting visual problems due to tissue occlusion. CONCLUSION: The study shows the potential benefits of an additional actuated imaging probe when used in conjunction with traditional surgical instruments to perform surgical tasks requiring visualization from multiple orientations and workspaces.

Efficacy of fusion imaging for immediate post-ablation assessment of malignant liver neoplasms: A systematic review.

BACKGROUND: Percutaneous thermal ablation has become the preferred therapeutic treatment option for liver cancers that cannot be resected. Since ablative zone tissue changes over time, it becomes challenging to determine therapy effectiveness over an extended period. Thus, an immediate post-procedural evaluation of the ablation zone is crucial, as it could influence the need for a second-look treatment or follow-up plan. Assessing treatment response immediately after ablation is essential to attain favorable outcomes. This study examines the efficacy of image fusion strategies immediately post-ablation in liver neoplasms to determine therapeutic response. METHODOLOGY: A comprehensive systematic search using PRISMA methodology was conducted using EMBASE, MEDLINE (via PUBMED), and Cochrane Library Central Registry electronic databases to identify articles that assessed the immediate post-ablation response in malignant hepatic tumors with fusion imaging (FI) systems. The data were retrieved on relevant clinical characteristics, including population demographics, pre-intervention clinical history, lesion characteristics, and intervention type. For the outcome metrics, variables such as average fusion time, intervention metrics, technical success rate, ablative safety margin, supplementary ablation rate, technical efficacy rate, LTP rates, and reported complications were extracted. RESULTS: Twenty-two studies were included for review after fulfilling the study eligibility criteria. FI's immediate technical success rate ranged from 81.3% to 100% in 17/22 studies. In 16/22 studies, the ablative safety margin was assessed immediately after ablation. Supplementary ablation was performed in 9 studies following immediate evaluation by FI. In 15/22 studies, the technical effectiveness rates during the first follow-up varied from 89.3% to 100%. CONCLUSION: Based on the studies included, we found that FI can accurately determine the immediate therapeutic response in liver cancer ablation image fusion and could be a feasible intraprocedural tool for determining short-term post-ablation outcomes in unresectable liver neoplasms. There are some technical challenges that limit the widespread adoption of FI techniques. Large-scale randomized trials are warranted to improve on existing protocols. Future research should emphasize improving FI's technological capabilities and clinical applicability to a broader range of tumor types and ablation procedures.

Evaluation of user-interfaces for controlling movements of virtual minimally invasive surgical instruments.

BACKGROUND: Recent tele-mentoring technologies for minimally invasive surgery (MIS) augments the operative field with movements of virtual surgical instruments as visual cues. The objective of this work is to assess different user-interfaces that effectively transfer mentor's hand gestures to the movements of virtual surgical instruments. METHODS: A user study was conducted to assess three different user-interface devices (Oculus-Rift, SpaceMouse, Touch Haptic device) under various scenarios. The devices were integrated with a MIS tele-mentoring framework for control of both manual and robotic virtual surgical instruments. RESULTS: The user study revealed that Oculus Rift is preferred during robotic scenarios, whereas the touch haptic device is more suitable during manual scenarios for tele-mentoring. CONCLUSION: A user-interface device in the form of a stylus controlled by fingers for pointing in 3D space is more suitable for manual MIS, whereas a user-interface that can be moved and oriented easily in 3D space by wrist motion is more suitable for robotic MIS.

A lightweight neural network with multiscale feature enhancement for liver CT segmentation.

Segmentation of abdominal Computed Tomography (CT) scan is essential for analyzing, diagnosing, and treating visceral organ diseases (e.g., hepatocellular carcinoma). This paper proposes a novel neural network (Res-PAC-UNet) that employs a fixed-width residual UNet backbone and Pyramid Atrous Convolutions, providing a low disk utilization method for precise liver CT segmentation. The proposed network is trained on medical segmentation decathlon dataset using a modified surface loss function. Additionally, we evaluate its quantitative and qualitative performance; the Res16-PAC-UNet achieves a Dice coefficient of 0.950 ± 0.019 with less than half a million parameters. Alternatively, the Res32-PAC-UNet obtains a Dice coefficient of 0.958 ± 0.015 with an acceptable parameter count of approximately 1.2 million.

Feasibility and Efficacy of Fusion Imaging Systems for Immediate Post Ablation Assessment of Liver Neoplasms: Protocol for a Rapid Systematic Review.

INTRODUCTION: Percutaneous thermal ablation is widely adopted as a curative treatment approach for unresectable liver neoplasms. Accurate immediate assessment of therapeutic response post-ablation is critical to achieve favourable outcomes. The conventional technique of side-by-side comparison of pre- and post-ablation scans is challenging and hence there is a need for improved methods, which will accurately evaluate the immediate post-therapeutic response. OBJECTIVES AND SIGNIFICANCE: This review summarizes the findings of studies investigating the feasibility and efficacy of the fusion imaging systems in the immediate post-operative assessment of the therapeutic response to thermal ablation in liver neoplasms. The findings could potentially empower the clinicians with updated knowledge of the state-of-the-art in the assessment of treatment response for unresectable liver neoplasms. METHODS AND ANALYSIS: A rapid review will be performed on publicly available major electronic databases to identify articles reporting the feasibility and efficacy of the fusion imaging systems in the immediate assessment of the therapeutic response to thermal ablation in liver neoplasms. The risk of bias and quality of articles will be assessed using the Cochrane risk of bias tool 2.0 and Newcastle Ottawa tool. ETHICS AND DISSEMINATION: Being a review, we do not anticipate the need for any approval from the Institutional Review Board. The outcomes of this study will be published in a peer-reviewed journal. HIGHLIGHTS: Evaluation of the therapeutic response in liver neoplasms immediately post-ablation is critical to achieve favourable patient outcomes. We will examine the feasibility and technical efficacy of different fusion imaging systems in assessing the immediate treatment response post-ablation. The findings are expected to guide the clinicians with updated knowledge on the state-of-the-art when assessing the immediate treatment response for unresectable liver neoplasms.

Leveraging hallmark Alzheimer's molecular targets using phytoconstituents: Current perspective and emerging trends.

Alzheimer's disease (AD), a type of dementia, severely distresses different brain regions. Characterized by various neuropathologies, it interferes with cognitive functions and neuropsychiatrical controls. This progressive deterioration has negative impacts not only on an individual's daily activity but also on social and occupational life. The pharmacological approach has always remained in the limelight for the treatment of AD. However, this approach is condemned with several side effects. Henceforth, a change in treatment approach has become crucial. Plant-based natural products are garnering special attention due to lesser side effects associated with their use. The current review emphasizes the anti-AD properties of phytoconstituents, throws light on those under clinical trials, and compiles information on their specific mode of actions against AD-related different neuropathologies. The phytoconstituents alone or in combinations will surely help discover new potent drugs for the effective treatment of AD with lesser side effects than the currently available pharmacological treatment.

Emerging Technologies for In Vitro Inhalation Toxicology.

Respiratory toxicology remains a major research area in the 21st century since current scenario of airborne viral infection transmission and pollutant inhalation is expected to raise the annual morbidity beyond 2 million. Clinical and epidemiological research connecting human exposure to air contaminants to understand adverse pulmonary health outcomes is, therefore, an immediate subject of human health assessment. Important observations in defining systemic effects of environmental contaminants on inhalation metabolic dysfunction, liver health, and gastrointestinal tract have been well explored with in vivo models. In this review, a framework is provided, a paradigm is established about inhalation toxicity testing in vitro, and a brief overview of breathing Lungs-on-Chip (LoC) as design concepts is given. The optimized bioengineering approaches and microfluidics with their fundamental pros, and cons are presented. There are different strategies that researchers apply to inhalation toxicity studies to assess a variety of inhalable substances and relevant LoC approaches. A case study from published literature and frame arguments about reproducibility as well as in vitro/in vivo correlations are discussed. Finally, the opportunities and challenges in soft robotics, systems inhalation toxicology approach integrating bioengineering, machine learning, and artificial intelligence to address a multitude model for future toxicology are discussed.

Towards development of a tele-mentoring framework for minimally invasive surgeries.

BACKGROUND: Tele-mentoring facilitates the transfer of surgical knowledge. The objective of this work is to develop a tele-mentoring framework that enables a specialist surgeon to mentor an operating surgeon by transferring information in a form of surgical instruments' motion required during a minimally invasive surgery. METHOD: A tele-mentoring framework is developed to transfer video stream of the surgical field, poses of the scope and port placement from the operating room to a remote location. From the remote location, the motion of virtual surgical instruments augmented onto the surgical field is sent to the operating room. RESULTS: The proposed framework is suitable to be integrated with laparoscopic as well as robotic surgeries. It takes on average 1.56 s to send information from the operating room to the remote location and 0.089 s for vice versa over a local area network. CONCLUSIONS: The work demonstrates a tele-mentoring framework that enables a specialist surgeon to mentor an operating surgeon during a minimally invasive surgery.

Emerging Application of Nanorobotics and Artificial Intelligence To Cross the BBB: Advances in Design, Controlled Maneuvering, and Targeting of the Barriers.

The blood-brain barrier (BBB) is a prime focus for clinicians to maintain the homeostatic function in health and deliver the theranostics in brain cancer and number of neurological diseases. The structural hierarchy and in situ biochemical signaling of BBB neurovascular unit have been primary targets to recapitulate into the in vitro modules. The microengineered perfusion systems and development in 3D cellular and organoid culture have given a major thrust to BBB research for neuropharmacology. In this review, we focus on revisiting the nanoparticles based bimolecular engineering to enable them to maneuver, control, target, and deliver the theranostic payloads across cellular BBB as nanorobots or nanobots. Subsequently we provide a brief outline of specific case studies addressing the payload delivery in brain tumor and neurological disorders (e.g., Alzheimer's disease, Parkinson's disease, multiple sclerosis, etc.). In addition, we also address the opportunities and challenges across the nanorobots' development and design. Finally, we address how computationally powered machine learning (ML) tools and artificial intelligence (AI) can be partnered with robotics to predict and design the next generation nanorobots to interact and deliver across the BBB without causing damage, toxicity, or malfunctions. The content of this review could be references to multidisciplinary science to clinicians, roboticists, chemists, and bioengineers involved in cutting-edge pharmaceutical design and BBB research.

End-user evaluation of software-generated intervention planning environment for transrectal magnetic resonance-guided prostate biopsies.

BACKGROUND: This study presents user evaluation studies to assess the effect of information rendered by an interventional planning software on the operator's ability to plan transrectal magnetic resonance (MR)-guided prostate biopsies using actuated robotic manipulators. METHODS: An intervention planning software was developed based on the clinical workflow followed for MR-guided transrectal prostate biopsies. The software was designed to interface with a generic virtual manipulator and simulate an intervention environment using 2D and 3D scenes. User studies were conducted with urologists using the developed software to plan virtual biopsies. RESULTS: User studies demonstrated that urologists with prior experience in using 3D software completed the planning less time. 3D scenes were required to control all degrees-of-freedom of the manipulator, while 2D scenes were sufficient for planar motion of the manipulator. CONCLUSIONS: The study provides insights on using 2D versus 3D environment from a urologist's perspective for different operational modes of MR-guided prostate biopsy systems.

Evaluation of how users interface with holographic augmented reality surgical scenes: Interactive planning MR-Guided prostate biopsies.

BACKGROUND: User interfaces play a vital role in the planning and execution of an interventional procedure. The objective of this study is to investigate the effect of using different user interfaces for planning transrectal robot-assisted MR-guided prostate biopsy (MRgPBx) in an augmented reality (AR) environment. METHOD: End-user studies were conducted by simulating an MRgPBx system with end- and side-firing modes. The information from the system to the operator was rendered on HoloLens as an output interface. Joystick, mouse/keyboard, and holographic menus were used as input interfaces to the system. RESULTS: The studies indicated that using a joystick improved the interactive capacity and enabled operator to plan MRgPBx in less time. It efficiently captures the operator's commands to manipulate the augmented environment representing the state of MRgPBx system. CONCLUSIONS: The study demonstrates an alternative to conventional input interfaces to interact and manipulate an AR environment within the context of MRgPBx planning.

Moving object tracking in clinical scenarios: application to cardiac surgery and cerebral aneurysm clipping.

BACKGROUND AND OBJECTIVES: Surgical procedures such as laparoscopic and robotic surgeries are popular since they are invasive in nature and use miniaturized surgical instruments for small incisions. Tracking of the instruments (graspers, needle drivers) and field of view from the stereoscopic camera during surgery could further help the surgeons to remain focussed and reduce the probability of committing any mistakes. Tracking is usually preferred in computerized video surveillance, traffic monitoring, military surveillance system, and vehicle navigation. Despite the numerous efforts over the last few years, object tracking still remains an open research problem, mainly due to motion blur, image noise, lack of image texture, and occlusion. Most of the existing object tracking methods are time-consuming and less accurate when the input video contains high volume of information and more number of instruments. METHODS: This paper presents a variational framework to track the motion of moving objects in surgery videos. The key contributions are as follows: (1) A denoising method using stochastic resonance in maximal overlap discrete wavelet transform is proposed and (2) a robust energy functional based on Bhattacharyya coefficient to match the target region in the first frame of the input sequence with the subsequent frames using a similarity metric is developed. A modified affine transformation-based registration is used to estimate the motion of the features following an active contour-based segmentation method to converge the contour resulted from the registration process. RESULTS AND CONCLUSION: The proposed method has been implemented on publicly available databases; the results are found satisfactory. Overlap index (OI) is used to evaluate the tracking performance, and the maximum OI is found to be 76% and 88% on private data and public data sequences.